Authors: Tienyu Zuo
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Meta-learning from Learning Curves: Challenge Design and Baseline Results, Nguyen et al, 2022, IJCNN.
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Exploration With Task Information for Meta Reinforcement Learning, Peng et al, 2021, IEEE Trans. NNLS.
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Meta-Learning-Based Deep Reinforcement Learning for Multiobjective Optimization Problems, Zhang et al, 2022, IEEE Trans. NNLS.
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Meta-Reinforcement Learning With Dynamic Adaptiveness Distillation, Hu et al, 2021, IEEE Trans. NNLS.
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Meta-Reinforcement Learning in Non-Stationary and Dynamic Environments, Bing et al, 2022, IEEE Trans. PAMI.
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MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning, Gupta et al, 2021, ICML.
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Prioritized Sampling with Intrinsic Motivation in Multi-Task Reinforcement Learning, D'Eramo et al, 2022, IJCNN.
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A Multi-Task Learning Framework for Head Pose Estimation under Target Motion, Yan et al, 2015, IEEE Trans. PAMI.
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Multi-Task Reinforcement Learning in Reproducing Kernel Hilbert Spaces via Cross-Learning, Cerviño et al, 2021, IEEE Trans. SP.
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Multi-Task Reinforcement Learning with Soft Modularization, Yang et al, 2020, NIPS.
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Provably efficient multi-task reinforcement learning with model transfer, Zhang et al, 2021, NIPS.
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Multi-Task Deep Reinforcement Learning with PopArt, Hessel et al, 2019, AAAI.
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H-DQN: Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation, Kulkarni et al, 2016, NIPS.
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HierRL: Hierarchical Reinforcement Learning for Task Scheduling in Distributed Systems, Guan et al, 2022, IJCNN.
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Data-Efficient Hierarchical Reinforcement Learning, Nachum et al, 2018, NIPS.
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FeUdal Networks for Hierarchical Reinforcement Learning, Vezhnevets et al, 2017, ICML.
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Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards, Li et al, 2019, NIPS.
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A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems, Ma et al, 2021, NIPS.
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Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning, Qin et al, 2019, IJCAI.
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A City-Wide Crowdsourcing Delivery System with Reinforcement Learning, Ding et al, 2021.
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Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching, Wang et al, 2018, ICDM.
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Combinatorial Optimization Meets Reinforcement Learning: Effective Taxi Order Dispatching at Large-Scale, Tong et al, 2021, IEEE Trans. KDE.
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An Integrated Reinforcement Learning and Centralized Programming Approach for Online Taxi Dispatching, Liang et al, 2021, IEEE Trans. NNLS.
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Context-Aware Taxi Dispatching at City-Scale Using Deep Reinforcement Learning, Liu et al, 2020, IEEE Trans. ITS.
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A Learning and Operation Planning Method for Uber Energy Storage System: Order Dispatch, Tao et al, 2022, IEEE Trans. ITS.
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Distributed Q -Learning-Based Online Optimization Algorithm for Unit Commitment and Dispatch in Smart Grid, Li et al, 2019, IEEE Trans. Cyb.
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Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning, Lin et al, 2018, KDD.
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PassGoodPool: Joint Passengers and Goods Fleet Management With Reinforcement Learning Aided Pricing, Matching, and Route Planning, Manchella et al, 2021, IEEE Trans. ITS.
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Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem, Holler et al, 2018, ICDM.
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Supply-Demand-aware Deep Reinforcement Learning for Dynamic Fleet Management, Zheng et al, 2022.
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AdaPool: A Diurnal-Adaptive Fleet Management Framework Using Model-Free Deep Reinforcement Learning and Change Point Detection, Haliem et al, 2021, IEEE Trans. ITS.
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CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms, Jin et al, 2019, CIKM.
- Reinforcement-Learning- and Belief-Learning-Based Double Auction Mechanism for Edge Computing Resource Allocation, Li et al, 2019, IEEE IoT Journal.
- Intelligent EV Charging for Urban Prosumer Communities: An Auction and Multi-Agent Deep Reinforcement Learning Approach, Zou et al, 2022, IEEE Trans. NSM.
- Comparisons of Auction Designs through Multi-Agent Learning in Peer-to-Peer Energy Trading, Zhao et al, 2022, IEEE Trans. SG.
- Coordination for Multi-Energy Microgrids Using Multi-Agent Reinforcement Learning, Qiu et al, 2022, IEEE Trans. II.
- Multi-Agent Reinforcement Learning for Automated Peer-to-Peer Energy Trading in Double-Side Auction Market, Qiu et al, 2021, IJCAI.